AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phosphopentomutase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q96G03

UPID:

PGM2_HUMAN

Alternative names:

Glucose phosphomutase 2; Phosphodeoxyribomutase; Phosphoglucomutase-2

Alternative UPACC:

Q96G03; B4E0G8; Q53FP5; Q5QTR0; Q9H0P9; Q9NV22

Background:

Phosphopentomutase, known by its alternative names Glucose phosphomutase 2, Phosphodeoxyribomutase, and Phosphoglucomutase-2, plays a crucial role in cellular metabolism. It catalyzes the conversion of ribose-1-phosphate and deoxyribose-1-phosphate into their 5-phosphopentose counterparts and facilitates the interconversion of glucose-1-phosphate into glucose-6-phosphate, albeit with lower efficiency. Its activity extends to a minor glucose 1,6-bisphosphate synthase function, suggesting a versatile enzymatic profile.

Therapeutic significance:

Understanding the role of Phosphopentomutase could open doors to potential therapeutic strategies. Its involvement in fundamental metabolic pathways highlights its potential as a target for metabolic disorders, offering a promising avenue for drug discovery and development.

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